中文版 | English
Title

Impacts of simplifying articulation movements imagery to speech imagery BCI performance

Author
Corresponding AuthorChen, Fei
Publication Years
2023-02-01
DOI
Source Title
ISSN
1741-2560
EISSN
1741-2552
Volume20Issue:1
Abstract
Objective. Speech imagery (SI) can be used as a reliable, natural, and user-friendly activation task for the development of brain-computer interface (BCI), which empowers individuals with severe disabilities to interact with their environment. The functional near-infrared spectroscopy (fNIRS) is advanced as one of the most suitable brain imaging methods for developing BCI systems owing to its advantages of being non-invasive, portable, insensitive to motion artifacts, and having relatively high spatial resolution. Approach. To improve the classification performance of SI BCI based on fNIRS, a novel paradigm was developed in this work by simplifying the articulation movements in SI to make the articulation movement differences clearer between different words imagery tasks. A SI BCI was proposed to directly answer questions by covertly rehearsing the word '(sic)' or '(sic)' ('yes' or 'no' in English), and an unconstrained rest task also was contained in this BCI. The articulation movements of SI were simplified by retaining only the movements of the jaw and lips of vowels in Chinese Pinyin for words '(sic)' and '(sic)'. Main results. Compared with conventional speech imagery, simplifying the articulation movements in SI could generate more different brain activities among different tasks, which led to more differentiable temporal features and significantly higher classification performance. The average 3-class classification accuracies of the proposed paradigm across all 20 participants reached 69.6% and 60.2% which were about 10.8% and 5.6% significantly higher than those of the conventional SI paradigm operated in the 0-10 s and 0-2.5 s time windows, respectively. Significance. These results suggested that simplifying the articulation movements in SI is promising for improving the classification performance of intuitive BCIs based on speech imagery.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
Funding Project
Shenzhen Sustainable Support Program for High-level University[20200925154002001]
WOS Research Area
Engineering ; Neurosciences & Neurology
WOS Subject
Engineering, Biomedical ; Neurosciences
WOS Accession No
WOS:000919292200001
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:1
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/430987
DepartmentDepartment of Electrical and Electronic Engineering
Affiliation
1.Harbin Inst Technol, Sch Elect & Informat Engn, Harbin, Peoples R China
2.Southern Univ Sci & Technol, Dept Elect & Elect Engn, Shenzhen, Peoples R China
First Author AffilicationDepartment of Electrical and Electronic Engineering
Corresponding Author AffilicationDepartment of Electrical and Electronic Engineering
Recommended Citation
GB/T 7714
Guo, Zengzhi,Chen, Fei. Impacts of simplifying articulation movements imagery to speech imagery BCI performance[J]. Journal of Neural Engineering,2023,20(1).
APA
Guo, Zengzhi,&Chen, Fei.(2023).Impacts of simplifying articulation movements imagery to speech imagery BCI performance.Journal of Neural Engineering,20(1).
MLA
Guo, Zengzhi,et al."Impacts of simplifying articulation movements imagery to speech imagery BCI performance".Journal of Neural Engineering 20.1(2023).
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